


"""simple docstring"""



import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest

from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import ArrayaD, ClassLabel, Features, Image, Value
from datasets.features.features import ArrayaDExtensionType, cast_to_python_objects
from datasets.keyhash import DuplicatedKeysError, InvalidKeyError

from .utils import require_pil







class    __a						( __snake_case							):







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			pa.array(TypedSequence([1, 2, 3]   )   )
					self.assertEqual(arr.type      ,	pa.intaa()   )







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					with self.assertRaises(UpperCAmelCase   ):
						lowerCAmelCase_      							=			pa.array(TypedSequence([1, 2, 3]   )      ,	type=pa.intaa()   )







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					with self.assertRaises(UpperCAmelCase   ):
						lowerCAmelCase_      							=			pa.array(TypedSequence([1, 2, 3]      ,	try_type=Value('''bool'''   )      ,	type=Value('''int64'''   )   )   )







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			pa.array(TypedSequence([1, 2, 3]      ,	type=Value('''int32'''   )   )   )
					self.assertEqual(arr.type      ,	pa.intaa()   )







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					with self.assertRaises((TypeError, pa.lib.ArrowInvalid)   ):
						lowerCAmelCase_      							=			pa.array(TypedSequence(['''foo''', '''bar''']      ,	type=Value('''int64'''   )   )   )







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			pa.array(TypedSequence([1, 2, 3]      ,	try_type=Value('''int32'''   )   )   )
					self.assertEqual(arr.type      ,	pa.intaa()   )







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			pa.array(TypedSequence(['''foo''', '''bar''']      ,	try_type=Value('''int64'''   )   )   )
					self.assertEqual(arr.type      ,	pa.string()   )







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			pa.array(TypedSequence([[[1, 2, 3]]]      ,	type=ArrayaD((1, 3)      ,	'''int64'''   )   )   )
					self.assertEqual(arr.type      ,	ArrayaDExtensionType((1, 3)      ,	'''int64'''   )   )







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					with self.assertRaises((TypeError, pa.lib.ArrowInvalid)   ):
						lowerCAmelCase_      							=			pa.array(TypedSequence(['''foo''', '''bar''']      ,	type=ArrayaD((1, 3)      ,	'''int64'''   )   )   )







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			pa.array(TypedSequence([[[1, 2, 3]]]      ,	try_type=ArrayaD((1, 3)      ,	'''int64'''   )   )   )
					self.assertEqual(arr.type      ,	ArrayaDExtensionType((1, 3)      ,	'''int64'''   )   )







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			pa.array(TypedSequence(['''foo''', '''bar''']      ,	try_type=ArrayaD((1, 3)      ,	'''int64'''   )   )   )
					self.assertEqual(arr.type      ,	pa.string()   )







				@require_pil
				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					import PIL.Image

					lowerCAmelCase_      							=			PIL.Image.fromarray(np.arange(10      ,	dtype=np.uinta   ).reshape(2      ,	5   )   )
					with patch(
					    '''datasets.arrow_writer.cast_to_python_objects'''      ,	side_effect=UpperCAmelCase   ) as mock_cast_to_python_objects:
						lowerCAmelCase_      							=			pa.array(TypedSequence([{'''path''': None, '''bytes''': b'''image_bytes'''}, pil_image]      ,	type=Image()   )   )
						lowerCAmelCase_							,	lowerCAmelCase_      							=			mock_cast_to_python_objects.call_args_list[-1]
						self.assertIn('''optimize_list_casting'''      ,	UpperCAmelCase   )
						self.assertFalse(kwargs['''optimize_list_casting''']   )




def      UpperCAmelCase     (       _lowercase :   Tuple			,   _lowercase :   int	)						-> List[str]:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.BufferReader(_lowercase	) if isinstance(_lowercase			,   pa.Buffer	) else pa.memory_map(_lowercase	)
	lowerCAmelCase_      							=			pa.ipc.open_stream(_lowercase	)
	lowerCAmelCase_      							=			f.read_all()
	assert len(pa_table.to_batches()	) == expected_num_chunks
	assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
	del pa_table
@pytest.mark.parametrize('''writer_batch_size'''			,   [None, 1, 1_0]	)
@pytest.mark.parametrize(
    '''fields'''			,   [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]	)
def      UpperCAmelCase     (       _lowercase :   Dict			,   _lowercase :   List[Any]	)						-> Any:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.BufferOutputStream()
	lowerCAmelCase_      							=			pa.schema(_lowercase	) if fields else None
	with ArrowWriter(stream=_lowercase			,   schema=_lowercase			,   writer_batch_size=_lowercase	) as writer:
		writer.write({'''col_1''': '''foo''', '''col_2''': 1}	)
		writer.write({'''col_1''': '''bar''', '''col_2''': 2}	)
		lowerCAmelCase_							,	lowerCAmelCase_      							=			writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	if not fields:
		lowerCAmelCase_      							=			{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
	assert writer._schema == pa.schema(_lowercase			,   metadata=writer._schema.metadata	)
	_check_output(output.getvalue()			,   expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)
def      UpperCAmelCase     (       )						-> Dict:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.BufferOutputStream()
	lowerCAmelCase_      							=			Features({'''labels''': ClassLabel(names=['''neg''', '''pos''']	)}	)
	with ArrowWriter(stream=_lowercase			,   features=_lowercase	) as writer:
		writer.write({'''labels''': 0}	)
		writer.write({'''labels''': 1}	)
		lowerCAmelCase_							,	lowerCAmelCase_      							=			writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	assert writer._schema == features.arrow_schema
	assert writer._schema.metadata == features.arrow_schema.metadata
	lowerCAmelCase_      							=			pa.BufferReader(output.getvalue()	)
	lowerCAmelCase_      							=			pa.ipc.open_stream(_lowercase	)
	lowerCAmelCase_      							=			f.read_all()
	lowerCAmelCase_      							=			pa_table.schema
	assert pa_table.num_rows == 2
	assert schema == features.arrow_schema
	assert schema.metadata == features.arrow_schema.metadata
	assert features == Features.from_arrow_schema(_lowercase	)
@pytest.mark.parametrize('''writer_batch_size'''			,   [None, 1, 1_0]	)
def      UpperCAmelCase     (       _lowercase :   Optional[Any]	)						-> Optional[int]:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.BufferOutputStream()
	with ArrowWriter(
	    stream=_lowercase			,   writer_batch_size=_lowercase			,   hash_salt='''split_name'''			,   check_duplicates=_lowercase			,   ) as writer:
		with pytest.raises(_lowercase	):
			writer.write({'''col_1''': '''foo''', '''col_2''': 1}			,   key=[1, 2]	)
			lowerCAmelCase_							,	lowerCAmelCase_      							=			writer.finalize()
@pytest.mark.parametrize('''writer_batch_size'''			,   [None, 2, 1_0]	)
def      UpperCAmelCase     (       _lowercase :   Any	)						-> Union[str, Any]:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.BufferOutputStream()
	with ArrowWriter(
	    stream=_lowercase			,   writer_batch_size=_lowercase			,   hash_salt='''split_name'''			,   check_duplicates=_lowercase			,   ) as writer:
		with pytest.raises(_lowercase	):
			writer.write({'''col_1''': '''foo''', '''col_2''': 1}			,   key=1_0	)
			writer.write({'''col_1''': '''bar''', '''col_2''': 2}			,   key=1_0	)
			lowerCAmelCase_							,	lowerCAmelCase_      							=			writer.finalize()
@pytest.mark.parametrize('''writer_batch_size'''			,   [None, 2, 1_0]	)
def      UpperCAmelCase     (       _lowercase :   Union[str, Any]	)						-> Tuple:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.BufferOutputStream()
	with ArrowWriter(
	    stream=_lowercase			,   writer_batch_size=_lowercase			,   hash_salt='''split_name'''			,   check_duplicates=_lowercase			,   ) as writer:
		writer.write({'''col_1''': '''foo''', '''col_2''': 1}			,   key=1	)
		writer.write({'''col_1''': '''bar''', '''col_2''': 2}			,   key=2	)
		lowerCAmelCase_							,	lowerCAmelCase_      							=			writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	_check_output(output.getvalue()			,   expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)
@pytest.mark.parametrize('''writer_batch_size'''			,   [None, 1, 1_0]	)
@pytest.mark.parametrize(
    '''fields'''			,   [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]	)
def      UpperCAmelCase     (       _lowercase :   Optional[Any]			,   _lowercase :   Optional[int]	)						-> Union[str, Any]:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.BufferOutputStream()
	lowerCAmelCase_      							=			pa.schema(_lowercase	) if fields else None
	with ArrowWriter(stream=_lowercase			,   schema=_lowercase			,   writer_batch_size=_lowercase	) as writer:
		writer.write_batch({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}	)
		writer.write_batch({'''col_1''': [], '''col_2''': []}	)
		lowerCAmelCase_							,	lowerCAmelCase_      							=			writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	if not fields:
		lowerCAmelCase_      							=			{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
	assert writer._schema == pa.schema(_lowercase			,   metadata=writer._schema.metadata	)
	_check_output(output.getvalue()			,   expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)
@pytest.mark.parametrize('''writer_batch_size'''			,   [None, 1, 1_0]	)
@pytest.mark.parametrize(
    '''fields'''			,   [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]	)
def      UpperCAmelCase     (       _lowercase :   List[str]			,   _lowercase :   Any	)						-> Tuple:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.BufferOutputStream()
	lowerCAmelCase_      							=			pa.schema(_lowercase	) if fields else None
	with ArrowWriter(stream=_lowercase			,   schema=_lowercase			,   writer_batch_size=_lowercase	) as writer:
		writer.write_table(pa.Table.from_pydict({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}	)	)
		lowerCAmelCase_							,	lowerCAmelCase_      							=			writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	if not fields:
		lowerCAmelCase_      							=			{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
	assert writer._schema == pa.schema(_lowercase			,   metadata=writer._schema.metadata	)
	_check_output(output.getvalue()			,   expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)
@pytest.mark.parametrize('''writer_batch_size'''			,   [None, 1, 1_0]	)
@pytest.mark.parametrize(
    '''fields'''			,   [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]	)
def      UpperCAmelCase     (       _lowercase :   Optional[Any]			,   _lowercase :   Union[str, Any]	)						-> Optional[int]:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.BufferOutputStream()
	lowerCAmelCase_      							=			pa.schema(_lowercase	) if fields else None
	with ArrowWriter(stream=_lowercase			,   schema=_lowercase			,   writer_batch_size=_lowercase	) as writer:
		writer.write_row(pa.Table.from_pydict({'''col_1''': ['''foo'''], '''col_2''': [1]}	)	)
		writer.write_row(pa.Table.from_pydict({'''col_1''': ['''bar'''], '''col_2''': [2]}	)	)
		lowerCAmelCase_							,	lowerCAmelCase_      							=			writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	if not fields:
		lowerCAmelCase_      							=			{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
	assert writer._schema == pa.schema(_lowercase			,   metadata=writer._schema.metadata	)
	_check_output(output.getvalue()			,   expected_num_chunks=num_examples if writer_batch_size == 1 else 1	)
def      UpperCAmelCase     (       )						-> Dict:


	"""simple docstring"""




	with tempfile.TemporaryDirectory() as tmp_dir:
		lowerCAmelCase_      							=			{'''col_1''': pa.string(), '''col_2''': pa.intaa()}
		lowerCAmelCase_      							=			os.path.join(_lowercase			,   '''test.arrow'''	)
		with ArrowWriter(path=_lowercase			,   schema=pa.schema(_lowercase	)	) as writer:
			writer.write_batch({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}	)
			lowerCAmelCase_							,	lowerCAmelCase_      							=			writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		assert writer._schema == pa.schema(_lowercase			,   metadata=writer._schema.metadata	)
		_check_output(_lowercase			,   1	)
def      UpperCAmelCase     (       _lowercase :   Optional[Any]	)						-> int:


	"""simple docstring"""




	if pa.types.is_list(_lowercase	):
		return get_base_dtype(arr_type.value_type	)
	else:
		return arr_type
def      UpperCAmelCase     (       _lowercase :   List[Any]			,   _lowercase :   Union[str, Any]	)						-> int:


	"""simple docstring"""




	if isinstance(lst[0]			,   _lowercase	):
		change_first_primitive_element_in_list(lst[0]			,   _lowercase	)
	else:
		lowerCAmelCase_      							=			value
@pytest.mark.parametrize('''optimized_int_type, expected_dtype'''			,   [(None, pa.intaa()), (Value('''int32'''	), pa.intaa())]	)
@pytest.mark.parametrize('''sequence'''			,   [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]	)
def      UpperCAmelCase     (       _lowercase :   Optional[Any]			,   _lowercase :   List[str]			,   _lowercase :   Dict	)						-> List[Any]:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.array(TypedSequence(_lowercase			,   optimized_int_type=_lowercase	)	)
	assert get_base_dtype(arr.type	) == expected_dtype
@pytest.mark.parametrize(
    '''col, expected_dtype'''			,   [
        ('''attention_mask''', pa.inta()),
        ('''special_tokens_mask''', pa.inta()),
        ('''token_type_ids''', pa.inta()),
        ('''input_ids''', pa.intaa()),
        ('''other''', pa.intaa()),
    ]			,   )
@pytest.mark.parametrize('''sequence'''			,   [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]	)
def      UpperCAmelCase     (       _lowercase :   List[str]			,   _lowercase :   Optional[Any]			,   _lowercase :   Union[str, Any]	)						-> Optional[Any]:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.array(OptimizedTypedSequence(_lowercase			,   col=_lowercase	)	)
	assert get_base_dtype(arr.type	) == expected_dtype

	# not in range
	if col != "other":
		# avoids errors due to in-place modifications
		lowerCAmelCase_      							=			copy.deepcopy(_lowercase	)
		lowerCAmelCase_      							=			np.iinfo(expected_dtype.to_pandas_dtype()	).max + 1
		change_first_primitive_element_in_list(_lowercase			,   _lowercase	)
		lowerCAmelCase_      							=			pa.array(OptimizedTypedSequence(_lowercase			,   col=_lowercase	)	)
		assert get_base_dtype(arr.type	) == pa.intaa()
@pytest.mark.parametrize('''raise_exception'''			,   [False, True]	)
def      UpperCAmelCase     (       _lowercase :   Union[str, Any]			,   _lowercase :   str	)						-> Tuple:


	"""simple docstring"""




	lowerCAmelCase_      							=			str(tmp_path / '''dataset-train.arrow'''	)
	try:
		with ArrowWriter(path=_lowercase	) as writer:
			if raise_exception:
				raise pa.lib.ArrowInvalid()
			else:
				writer.stream.close()
	except pa.lib.ArrowInvalid:
		pass
	finally:
		assert writer.stream.closed
def      UpperCAmelCase     (       _lowercase :   Tuple	)						-> str:


	"""simple docstring"""




	lowerCAmelCase_      							=			'''mock://dataset-train.arrow'''
	with ArrowWriter(path=_lowercase			,   storage_options=mockfs.storage_options	) as writer:
		assert isinstance(writer._fs			,   type(_lowercase	)	)
		assert writer._fs.storage_options == mockfs.storage_options
		writer.write({'''col_1''': '''foo''', '''col_2''': 1}	)
		writer.write({'''col_1''': '''bar''', '''col_2''': 2}	)
		lowerCAmelCase_							,	lowerCAmelCase_      							=			writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	assert mockfs.exists(_lowercase	)
def      UpperCAmelCase     (       )						-> List[Any]:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.BufferOutputStream()
	with ParquetWriter(stream=_lowercase	) as writer:
		writer.write({'''col_1''': '''foo''', '''col_2''': 1}	)
		writer.write({'''col_1''': '''bar''', '''col_2''': 2}	)
		lowerCAmelCase_							,	lowerCAmelCase_      							=			writer.finalize()
	assert num_examples == 2
	assert num_bytes > 0
	lowerCAmelCase_      							=			pa.BufferReader(output.getvalue()	)
	lowerCAmelCase_      							=			pq.read_table(_lowercase	)
	assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
@require_pil
@pytest.mark.parametrize('''embed_local_files'''			,   [False, True]	)
def      UpperCAmelCase     (       _lowercase :   str			,   _lowercase :   Dict	)						-> Union[str, Any]:


	"""simple docstring"""




	import PIL.Image

	lowerCAmelCase_      							=			str(tmp_path / '''test_image_rgb.jpg'''	)
	PIL.Image.fromarray(np.zeros((5, 5)			,   dtype=np.uinta	)	).save(_lowercase			,   format='''png'''	)
	lowerCAmelCase_      							=			pa.BufferOutputStream()
	with ParquetWriter(
	    stream=_lowercase			,   features=Features({'''image''': Image()}	)			,   embed_local_files=_lowercase	) as writer:
		writer.write({'''image''': image_path}	)
		writer.finalize()
	lowerCAmelCase_      							=			pa.BufferReader(output.getvalue()	)
	lowerCAmelCase_      							=			pq.read_table(_lowercase	)
	lowerCAmelCase_      							=			pa_table.to_pydict()
	if embed_local_files:
		assert isinstance(out['''image'''][0]['''path''']			,   _lowercase	)
		with open(_lowercase			,   '''rb'''	) as f:
			assert out["image"][0]["bytes"] == f.read()
	else:
		assert out["image"][0]["path"] == image_path
		assert out["image"][0]["bytes"] is None





def      UpperCAmelCase     (       )						-> Optional[Any]:


	"""simple docstring"""




	lowerCAmelCase_      							=			pa.schema([pa.field('''col_1'''			,   pa.string()			,   nullable=_lowercase	)]	)
	lowerCAmelCase_      							=			pa.BufferOutputStream()
	with ArrowWriter(stream=_lowercase	) as writer:
		writer._build_writer(inferred_schema=_lowercase	)
		assert writer._schema == pa.schema([pa.field('''col_1'''			,   pa.string()	)]	)



"""simple docstring"""



from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader







class    __a						( __snake_case							):







				def __init__( self      ,	UpperCAmelCase      ,	UpperCAmelCase = None      ,	UpperCAmelCase = None      ,	UpperCAmelCase = True      ,	UpperCAmelCase = None      ,	UpperCAmelCase = False      ,	UpperCAmelCase = None      ,	UpperCAmelCase = True      ,	UpperCAmelCase = "arrow"      ,	**UpperCAmelCase      ,	):

					'''simple docstring'''






					super().__init__(
					    split=UpperCAmelCase      ,	features=UpperCAmelCase      ,	cache_dir=UpperCAmelCase      ,	keep_in_memory=UpperCAmelCase      ,	streaming=UpperCAmelCase      ,	**UpperCAmelCase      ,	)
					lowerCAmelCase_      							=			load_from_cache_file
					lowerCAmelCase_      							=			file_format
					lowerCAmelCase_      							=			Spark(
					    df=UpperCAmelCase      ,	features=UpperCAmelCase      ,	cache_dir=UpperCAmelCase      ,	working_dir=UpperCAmelCase      ,	**UpperCAmelCase      ,	)







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					if self.streaming:
						return self.builder.as_streaming_dataset(split=self.split   )
					lowerCAmelCase_      							=			None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
					self.builder.download_and_prepare(
					    download_mode=UpperCAmelCase      ,	file_format=self._file_format      ,	)
					return self.builder.as_dataset(split=self.split   )